REU Site: Biomedical Engineering in Simulations, Imaging, and Modeling (BME-SIM)

东卡罗来纳大学的生物医学工程模拟、成像和建模(BME-SIM)本科生研究体验(REU)网站为30名未被充分代表和未得到充分服务的学生提供真实的研究体验--包括女性、未被充分代表的少数族裔学生，以及其母校提供的研究机会有限的学生。让这些学生接触创新研究将提高研究生院的知名度，从而提高申请率，最终提高STEM研究生院的渠道。通过增加STEM专业人员的多样性扩大参与范围，促进科学进步。作为研究经验的补充，BME-SIM项目解决了工程的社会层面；因此，促进了一个更具包容性的环境和更多的归属感。这是通过该项目的创新领导力发展计划和促进积极的指导关系来实现的。REU计划的目标将通过使用模拟、成像和建模作为共同主线的多学科方法来实现。建模跨越规模和融合不同学科的能力将这种方法置于理解生物机制、系统动力学和最终改善健康的前沿。为了支持这一领域的发展，学生必须精通计算建模；这一领域在本科课程中很少涉及。因此，BME-SIM计划填补了这一劳动力缺口，同时提高了生理系统建模知识和培训下一代研究人员。BME-SIM REU的目标是为30名学生提供真实的研究体验，特别是代表不足和服务不足的人群，提高对研究生院的认识和应用。在项目结束时，学生应该取得以下五个成果：1)提高对研究过程的理解；2)提高对研究生院的认识；3)加强STEM职业道路；4)更好地认同工程师/科学家；以及5)提高领导能力。该项目将通过与国内机构导师合作以及在生物医学工程学会年会上重新建立联系，让参与者参与的时间超过10周的夏季研究体验。为了确保申请者的多样性，将从合作机构开始招生，其中包括历史上的黑人机构，一家服务于大量美国原住民人口的机构，以及全州范围内与社区大学的联系。BME-SIM的教育目标是通过使用模拟、成像和建模作为共同主线的多学科方法来实现的。开发模型有几个核心概念，如边界或初始条件以及验证。发展对这些统一主题的理解，使学生能够更好地在更广泛的背景下欣赏建模。与其他方法相比，计算建模有几个优势：1)生成和测试新的理论；2)估计难以测量的变量；3)结合特定对象的参数，通常来自非侵入性成像技术；以及4)为限制动物和人类使用的实验设计提供信息。每个REU项目都在其各自的模型或配套成像技术的开发、实施或精度方面取得进展。这种跨越尺度和融合不同学科的建模能力将这种方法置于理解生物机制、系统动力学和最终改善健康的前沿。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The Biomedical Engineering in Simulations, Imaging, and Modeling (BME-SIM) Research Experiences for Undergraduates (REU) Site at East Carolina University provides authentic research experiences to 30 targeted underrepresented and underserved students -- including women, underrepresented minority students, and students whose home institution offers limited research opportunities. Exposing these students to innovative research will raise awareness of graduate school; thereby, increasing application rates and ultimately the STEM graduate school pipeline. Broadening participation by increasing the diversity of STEM professionals promotes the progress of science. Complementary to the research experience, the BME-SIM program addresses the social dimensions of engineering; thus, promoting a more inclusive environment and increased sense of belonging. This is accomplished through both the program's innovative leadership development program and promotion of positive mentoring relationships. The REU program goals will be accomplished through a multidisciplinary approach using simulations, imaging, and modeling as a common thread. The power of modeling to span scales and blend different disciplines places this approach at the forefront for understanding biological mechanisms, system dynamics, and ultimately improving health. To support growth in this field, students must be adept in computational modeling; an area which is rarely addressed in undergraduate curricula. Thus, the BME-SIM program fills this workforce gap while advancing knowledge of modeling physiological systems and training the next generation of researchers.The goal of the BME-SIM REU is to provide authentic research experiences to 30 students, especially underrepresented and underserved populations, increasing awareness of and application to graduate school. At the end of the program students should achieve the following five outcomes: 1) improved understanding of the research process; 2) increased awareness of graduate school; 3) reinforcement of STEM career path; 4) greater identification as engineer/scientist; and 5) increased leadership capacities. The project will engage participants for longer than the 10-week summer research experience by both collaborating with home institution mentors and reconnecting at the Biomedical Engineering Society annual meeting. To ensure a diverse applicant pool, student recruitment will begin at partner institutions which include historically black institutions, an institution serving a large Native American population, and statewide connections with community colleges. The BME-SIM educational goals are accomplished through a multidisciplinary approach using simulations, imaging, and modeling as a common thread. There are several central concepts to developing models, such as boundary or initial conditions, and validation. Developing an understanding of these unifying themes enables students to better appreciate modeling in a broader context. Computational modeling offers several advantages over other approaches: 1) generate and test new theories; 2) estimate difficult to measure variables; 3) incorporate subject-specific parameters, generally derived from non-invasive imaging techniques; and 4) inform experimental designs limiting the use of animals and humans. Each REU project advances knowledge on the development, implementation, or accuracy of its respective model or companion imaging technique. The power of modeling to span scales and blend different disciplines places this approach at the forefront for understanding biological mechanisms, system dynamics, and ultimately improving health.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.